Emerging Trends in The Social and Behavioral Sciences

Spatial Attention

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Spatial Attention

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Spatial Attention
KYLE R. CAVE

Abstract
Visual perception requires selective filtering. The process of selecting a portion of the
visual input according to its location is described as spatial attention. Spatial attention has been measured with a wide variety of experimental techniques, including
spatial cuing, spatial probes, distractor interference, ERP, and SSVEP. The results
show that spatial attention sometimes takes the form of a gradient, with strong facilitation of processing within a central region and less facilitation and perhaps even
inhibition in the surround. The positioning of the attentional gradient is controlled
in part by a bottom-up system that directs attention to locations that differ from surrounding locations in basic features. There is also top-down direction of attention,
which favors locations with features matching a defined target. A variety of different experiments have demonstrated that attention can be allocated to a particular
location in the visual field, but another set of experiments show that attention can be
allocated to a visual object, and that attention that is directed to one part of an object
can spread to other parts of the same object. It is difficult to determine whether spatial
attention and object-based attention are controlled by the same system or by separate
systems. Determining the boundaries between different attentional systems should
become easier with the use of ERP data to provide precise timing information about
attentional processes, and fMRI to localize the brain regions controlling attention and
to measure attentional modulation of perceptual processing activity.

INTRODUCTION
Visual perception requires a combination of different processes, from early
processes that detect edges and infer surfaces, to later processes that match
the incoming input to memory representations to achieve recognition. The
earliest processes rely more on local comparisons that can be done with short
neural connections, but the later stages require integration of information
across large parts of the visual field, and thus require that information be
transmitted over long distances within the brain. The earlier processing
stages can produce more information than can be processed by the later
stages, and thus outputs of the earlier states must be filtered to select just
those parts with the highest potential for informativeness before they are
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

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routed to higher level mechanisms. This filtering process is often labeled as
“attention.”
Visual information arriving at the eye is spread across the two-dimensional
array of the retina, and this spatial organization is, to a large extent, maintained through the early stages of processing. Although many important
types of information are encoded in the early stages, location seems to
play a unique role in the organization of this information, as can be seen in
the spatial maps in the superior colliculus, the lateral geniculate nucleus,
primary visual cortex, and other brain regions serving vision. Location also
plays an important role in visual attention.
FOUNDATIONAL RESEARCH
SPATIAL CUING
One obvious reason why location is important in visual attention is that
visual information at the center of gaze is projected onto the fovea, which
has the highest spatial resolution within the retina. Thus, an important
part of selecting visual information is pointing the eyes toward the most
informative location in the environment. However, spatial cuing experiments (Eriksen & Hoffman, 1974; Posner, Snyder, & Davidson, 1980) have
shown that this overt attention is not the whole story. Even without moving
the eyes, it is possible to select one part of the visual field for faster, more
detailed processing. In these experiments, subjects are asked to keep their
eyes fixed at one location, while a cue appears some distance away, signaling
that an upcoming stimulus is most likely to appear at that location. This
cue causes covert attention to be allocated to that location, so that when the
stimulus does appear, subjects will respond to it more quickly if it is at the
cued location, and more slowly if it appears elsewhere.
There are two different aspects to this spatial cuing effect on attention.
If, throughout the course of the experiment, the stimulus appears more
often at the cued location than somewhere else, then the cue is providing useful information that can improve performance. In many of these
experiments, the cue is a symbol appearing at the center of gaze, and
subjects must interpret the symbol to know which location should be
attended. As long as the cue is informative, subjects have an incentive
to interpret the symbol and move their spatial attention to the indicated
location. This internally motivated cue use is called endogenous orienting.
In other cases, a cue can move attention to a location even if the subject
believes that it is uninformative. For this exogenous orienting, the cue
must be a flash or other salient stimulus located at the location to be
cued.

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SPATIAL PROBES
The simple spatial cuing paradigm has been a foundation on which other
more complex experimental procedures have been built. The stimulus that
triggers the response can be thought of as a probe that measures attention at
a location. Across trials, it can be applied to many different locations to produce a full picture of attentional allocation. The simple cue can be replaced
with other more complex stimuli coupled with tasks requiring spatial attention. The first example of this came from Hoffman and Nelson (1981), who
combined a probe task with a letter search task. Reports of the probe stimulus were more likely to be correct if it appeared near a correctly reported
target of the letter search. Spatial attention allocated to the letter target apparently also improved discrimination of the probe stimulus if it was in the same
vicinity. This experiment, and the many probe experiments that followed,
demonstrated the general nature of spatial attention, enhancing the processing of any stimulus appearing within the selected region. This spatial aspect
of attention led Posner, Snyder, and Davidson (1980) to compare attention to
a spotlight that illuminates just one selected part of the visual field.
FLANKERS AND DISTRACTOR INTERFERENCE
The importance of location in attention is made apparent by a technique used
by Eriksen and Eriksen (1974). They simply required subjects to identify a letter appearing in the middle of the visual field. Other letters appeared along
with the target letter, and although the locations of these letters made it clear
that they were not the target, these letters could affect the response if they
were close enough to the target location. If these flanker letters were associated with the same response as the target, then the response was faster, and
if the flankers were associated with a different response, then the response
was slower. If the flankers were close to the target (within 1∘ of visual angle),
they were able to activate responses to the point that they either facilitated or
competed with the response being activated by the target letter. This flanker
effect shows that spatial selection is not perfect, and that distractors are not
always fully excluded.
GRADIENT VERSUS MOVING SPOTLIGHT
Experiments by Downing (1988) and by Laberge and Brown (1989) showed
that attentional facilitation could take the form of a gradient, with stronger
perceptual sensitivity for locations nearer the cue, and a fall-off in sensitivity
with distance. Sperling and Weichselgartner (1995) argued that this area of
attentional facilitation can be deallocated from one location and reallocated to
a new location without selecting locations in between. For a detailed review

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of the relevant findings on shape and movement of the attentional gradient,
see Cave and Bichot (1999).
ATTENTIONAL CAPTURE AND BOTTOM-UP ATTENTIONAL CONTROL
One big challenge for the visual system is deciding where in the visual field to
allocate the gradient of spatial attention in order to be most effective. Given
that this decision must be made before visual processing is completed and
before objects have been identified, it has to be done with only partial information. This control of attention requires a balance between different factors,
but one important factor is the presence of featural variation in the visual
field. Spatial attention is often allocated to a location that differs from its
surrounding locations in the basic visual features present there. Attention is
often captured by a location with a red stimulus that is surrounded by green,
or a horizontal contour that is surrounded by vertical, or a moving object
that is surrounded by stationary objects. Experiments by Theeuwes (1992)
demonstrate that attention can be captured by unique features (singletons)
even if they are irrelevant to the current task.
This attentional capture shows the importance of stimulus-driven or
bottom-up factors in controlling attention. However, Folk, Remington, and
Johnston (1992) have shown that attentional capture can be prevented in
some circumstances. To reconcile these results, Bacon and Egeth (1994)
proposed that the attentional system can shift modes depending on the
needs of the task. When a target object differs from the distractors in some
basic feature, searchers may simply use “singleton detection mode,” in
which attention is captured by any item that has a unique feature that differs
from its surroundings. Thus, when Theeuwes’ subjects search for a shape
singleton (diamond target among circle distractors), their attention will be
captured by a color singleton (red among green). However, if the task makes
it difficult to find the target by singleton search, searchers may instead
switch to “feature search mode,” in which attention is allocated to those
locations that have a specific feature value known to belong to the target.
TOP-DOWN ATTENTIONAL GUIDANCE AND THE TARGET TEMPLATE
The ability to search for a specific feature is another important factor in
the control of spatial attention: Many visual tasks require that attention
be directed to locations that have a specific color, size, or other feature,
even though that feature may not be a unique singleton. This top-down
guidance toward known targets must be balanced against the bottom-up
capture by unique objects. The top-down guidance requires that some sort
of internal target definition be maintained in order to guide attention. This

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target representation has sometimes been called the “target template,”
although some tasks require that it be more general than implied by the
term “template.”
Because the target representation is active only for the course of a particular visual task and will change from on task to another, it is natural to
compare it to visual working memory, the temporary storage proposed by
Baddeley (2007) to hold visual information that is actively being used in cognitive tasks. Perhaps the target information that guides attention top-down is
stored in the same visual working memory that is used for other visual tasks
that require temporary storage. If the search target representation and visual
working memory are one and the same, then whenever something is stored
in visual working memory for a nonattentional task, we might expect attention to be captured by stimuli that match the stored information. This idea
has been tested with various different search and memory tasks. In some circumstances, holding an item in visual working memory does redirect search,
while in other circumstances it does not (Olivers, Peters, Houtkamp, & Roelfsema, 2011; Woodman, Carlisle, & Reinhart, 2013). There is some type of
link between visual working memory and the attention target representation, because one can interfere with the other under the right conditions, but
they are probably not one and the same thing.
OBJECT-BASED ATTENTION
Although location is very important in allocating attention, there is also
abundant evidence that attention can be shaped by object boundaries. When
two objects are superimposed, one can be selected over the other (Duncan,
1984), and when an attended object moves, attention can move with it
(Kahneman, Treisman, & Gibbs, 1992). These demonstrations have led to a
distinction between spatial attention, which is allocated to a location, and
object-based attention, which is allocated to an object representation.
Many of the experiments in object-based attention have focused on how
attention that is initially cued to one part of an object can spread to other
parts of the same object. Egly, Driver, and Rafal (1994) provided a useful
experimental paradigm for studying this aspect of object-based attention by
extending Posner’s cuing procedure. Posner originally placed two boxes in
the stimulus display (one on each side of fixation), and cued one of them as
the expected target location. Egly, Driver, and Rafal extended these boxes
to make them long narrow rectangles, and then cued just one end of one
rectangle. The test stimulus, to which subjects responded as quickly as
possible, appeared in one end of one of the two rectangles. Responses were
fastest when it appeared at the cued end, as expected from Posner’s original
experiments. However, responses were faster for a stimulus at the uncued

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end of the cued rectangle than for a stimulus on the uncued rectangle, even
though distance from the cue was the same for both stimuli. Attention at the
cued location spread to facilitate visual detection of other locations within
the same object. See Chen (2012) for a review of object-based attention.
Although this type of object-based attention is easy to demonstrate experimentally, it does seem to require that attention be spread broadly across
a large area (Goldsmith & Yeari, 2003), and that the objects be visible long
enough for them to be interpreted as separate objects (Chen & Cave, 2008).
Object-based attention also varies according to whether the stimulus configuration is described as one object or two (Chen, 1998). Thus, even though
the object organization of a scene can affect attention when the objects are
irrelevant to the task, encoding the object organization is apparently not a
necessary step in allocating attention.
The relationship between location-based attention and object-based attention is not clear. They could arise from separate attentional mechanisms
working at different processing stages within the visual system. Selection
that occurs within the early processing mechanisms of the lateral geniculate
nucleus and primary visual cortex could be responsible for location-based
attention, while selection among more abstract object representations in
temporal regions could be producing object-based attention. On the other
hand, there might be a single spatial selection mechanism, with the locations
that are selected being shaped by the perceived object organization. This
idea of a unified spatial/object selection is consistent with theories in which
attention is driven by an interaction between low level visual processing
and higher level object representations (Heinke, Mavritsaki, Backhaus, &
Kreyling, 2009).
VISUAL SEARCH
Cuing experiments, in which the target location is known or at least expected
in advance, have demonstrated both location selection and object selection.
As important as attention is in these relatively simple tasks, it is probably
even more important in search tasks, in which the target location is unknown
and the allocation of attention is probably much more complex in search.
Most search experiments do not address the role of spatial location in selection, but instead test the capacity limits of attention by adding more and more
objects to the search array. These search experiments have been important in
exploring the perceptual limitations that make attentional selection necessary (Treisman & Gelade, 1980; Wolfe 2007). Search experiments have been
the primary tool for determining which visual properties are identified early
in processing and can effectively guide attention (Wolfe & Horowitz, 2004).

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Although search has not been used as much to demonstrate the spatial
nature of visual selection, it is pretty clear that spatial selection plays a role
in search. Many visual search experiments elicit a combination of eye movements and covert attention. The eye movements are clearly an instance of
spatial selection, given that the goal of the eye movements is to direct the
fovea toward the selected location. The role of covert attention in search can
be studied by eliminating the eye movements, either by using an eyetracker
or by presenting the search array so briefly that an eye movement cannot
be programmed and executed before it disappears. Spatial selection can be
demonstrated in these covert search tasks with spatial probes: Probes at target locations or at locations that share target features show attentional facilitation, even though the probes do not share the target features, and are only
linked to those features by location (Kim & Cave, 1995).
CUTTING-EDGE RESEARCH
ERP, MEG, AND SSVEP
The history of research in spatial attention illustrates that much can be
learned with behavioral experiments measuring response times and accuracy. However, event-related potential (ERP) methods based on measuring
changes in electrical potential with scalp electrodes have provided a powerful tool for measuring how neural processing of visual signals changes
with attention (Luck, Woodman, & Vogel, 2000; Mangun & Hillyard, 1995).
The attentional enhancement of visual signals can be measured in ERPs
within 100 ms or so after a stimulus appears. ERP methods also provide a
way to measure attention at visual field locations that the subject is trying
to ignore, which cannot be done with spatial probes that require a response.
Also, experiments by Hopf et al. (2006) using a related method based
on magnetoencephelography (MEG) have provided key demonstrations
of the inhibitory attentional surround around attended locations, which
corresponds to behavioral findings by Cave and Zimmerman (1997) and by
Mounts (2000).
The electroencephalographic measurements used in ERP experiments can
also be used to record steady-state visual electric potentials (SSVEPs), which
can also reflect changes in neural activation caused by attention (Muller,
Malinowski, Gruber, & Hillyard, 2003). In this paradigm, each stimulus in
a visual display flickers at a different rate, and those stimulus oscillations
are carried by the neural signals encoding those stimuli. When a particular
stimulus is attended, the EEG signal will show a stronger oscillation at that
stimulus’ frequency. Thus, this method provides another way to measure
spatial attention without a response from the subject.

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SPLIT ATTENTION
Many of the experiments described here have started with the assumption
that spatial attention selects a single unified region within the visual field.
In fact, that assumption is built into the spotlight metaphor that drove early
attentional research. However, many visual tasks require comparing or conjoining stimuli at two or more separate visual field locations, and the question arises whether those multiple locations can be selected without selecting
distractor locations between them. A number of experiments have been presented over the years to demonstrate split attention, but it has been difficult
to determine whether attention is simultaneously selecting to locations, or is
moving quickly between them. Jans, Peters, and De Weerd (2010) have thoroughly reviewed these experiments and have tried to interpret them as the
product of a single focus of attention. The theoretical assumptions that are
necessary to defend the single attentional spotlight hypothesis require such
complex operations that the split attention alternative begins to sound more
plausible (Cave, Bush, & Taylor, 2010).
PERCEPTUAL LOAD VERSUS DILUTION
One of the more controversial general theories of attention comes from Nilli
Lavie (2005), who suggests that there is a fixed amount of attentional capacity
that can be allocated to different visual tasks, and that at any one moment,
all of it will be used. This means that if the current visual task is relatively
easy and uses only some of the available capacity (in other words, it has a
low perceptual load), the rest will be applied to processing distractor items
in the visual field, even though they are irrelevant to the current task. Lavie
provides supporting evidence for this perceptual load theory from a number of experiments. She shows that the interference from a salient distractor
decreases as the task requires processing of more items.
Perceptual load theory has faced a number of challenges. One of the more
notable comes from Tsal and Benoni (2010) and Wilson, Muroi, and MacLeod
(2011), who reject Lavie’s claim that it is the extra perceptual load from additional relevant display items that absorbs attentional capacity and limits distractor interference. Instead, they propose that whenever items are added
to the display, even if they are irrelevant to the task, they interfere with the
processing of other items. This alternative account is referred to as dilution.
Comparing the evidence for perceptual load theory against the evidence
for dilution is complicated by another factor, as pointed out by Chen and
Cave (2013). In these studies, the search array generally appears suddenly,
and these abrupt onsets have the effect of broadening the attentional zoom
to encompass the full display. When the display is presented in a way that
avoids the abrupt onsets, the results no longer show the general pattern of

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dilution. That does not mean that perceptual load theory prevails, as a number of other studies have challenged it, including one by Kyllingsbaek, Sy,
and Giesbrecht (2011) showing that adding distractor letters can take processing resources away from targets. There may be validity in Lavie’s general
claim that processing of distractors varies according to the demands of processing targets, but the whole story is probably more complicated.
LOCALIZING BRAIN MECHANISMS FOR SPATIAL ATTENTION
The focus here has been mainly on behavioral studies of attention, and on
ERP studies that provide timing information about the neural processing
underlying attention. These results can now be combined with a large number of functional MRI studies showing which brain regions are involved in
attentional selection. The relevant brain regions are often organized into two
categories. The “sites of attention” are those brain regions within the visual
system that are responsible for identifying objects, including primary visual
cortex (V1) and the ventral, or “what” pathway. The activity within these
regions is modulated according to attentional goals (Kastner & Pinsk, 2004).
That modulation seems to be controlled by another set of cortical regions
often described as “sources of attention,” which include frontal and parietal
regions that are linked together in such a way that they are often referred to
as the frontal-parietal network (Corbetta, Patel, & Shulman, 2008).
Interpretation of these studies of large-scale brain activation can be guided
by measurement of attentional effects on individual neurons (Moran &
Desimone, 1985). When these neuroscience findings are combined with the
decades of research on attentional performance described earlier, we have a
rich environment within which to construct detailed theories of attentional
selection.
KEY ISSUES FOR FUTURE RESEARCH
ATTENTIONAL ZOOM
Over the years, a number of detailed computational models have been proposed to explain how the attended location is chosen, but these models have
had less to say about how the size of the attended area can be adjusted according to the task. Nonetheless, there are clear demonstrations that attention
can zoom in to a small region for difficult tasks, and can pan out to select a
wide area for easier tasks (Eriksen & St. James, 1986; Laberge, 1983; Larsen &
Bundesen, 1978). More recently, Rijpkema, van Aalderen, Schwarzbach, and
Verstraten (2008) have used brain imaging to show that cortical regions with
different receptive field sizes can be activated to match the attentional zoom

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settings required for different visual tasks. Models of attention need to be
expanded to capture this adjustment of attentional zoom more fully.
DIFFERENTIATING ATTENTIONAL MECHANISMS
As noted earlier, it is usually difficult to determine the extent to which the
task of visual selection is divided across separate mechanisms. For instance,
are spatial attention and object attention performed by a single system or two
separate systems? Are there different selection mechanisms working at different levels of the hierarchy within the visual system? Or does attentional
selection require coordination between lower and higher levels of visual processing? The behavioral methods that have been used to explore these questions for some time can now be augmented with localization information
from fMRI and timing information from ERP studies in order to find the
boundaries between the different parts of the attentional system. This line of
enquiry may also provide a better understanding of the computational limitations within the visual system that make attentional selection necessary in
the first place.
ATTENTION AND CONSCIOUSNESS
Spatial attention seems to be necessary to prevent the visual system from
being overwhelmed by the amount of incoming retinal input to be processed.
However, it has been natural to assume that this selection mechanism also
serves as the gateway to visual consciousness. Perhaps everything that is
selected makes its way into our awareness, while everything not selected
remains outside of conscious. That assumption, however, is contradicted by
evidence showing that visual stimuli can be selected without making it into
awareness. One unusual example comes from Jiang, Costello, Huang, and
He (2006), in which nude images draw attention to their location without the
observer’s awareness. Thus, visual selection and consciousness must be separate, and even when a stimulus is selected within the visual system, it may
still not be able to pass through the higher level gateway into awareness.
Koch and Tsuchiya (2007) suggested that there might be a pathway for stimuli to enter consciousness without being selected by spatial attention, based
on the finding by Li, VanRullen, Koch, and Perona (2002) that animals and
vehicles could be detected in scenes while attention was occupied in a different part of the visual field. While it is clear that performance on the detection
tasks can be surprisingly good, it is not clear that it is done without any contribution from spatial attention (Cohen, Alvarez, & Nakayama, 2011). Thus, the
full relationship between spatial attention and conscious experience remains
to be fully worked out.

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invisual working memory: When it guides attention and when it does not. Trends
in Cognitive Sciences, 15, 327–334.
Posner, M. I., Snyder, C. R. R., & Davidson, B. J. (1980). Attention and the detection
of signals. Journal of Experimental Psychology: General, 109, 160–174.
Rijpkema, M., van Aalderen, S. I., Schwarzbach, J. V., & Verstraten, F. A. J. (2008). Activation patterns in visual cortex reveal receptive field size-dependent attentional
modulation. Brain Research, 1189, 90–96.
Sperling, G., & Weichselgartner, E. (1995). Episodic theory of the dynamics of spatial
attention. Psychological Review, 102, 503–532.
Theeuwes, J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51, 599–606.
Treisman, A., & Gelade, T. (1980). A feature integration theory of attention. Cognitive
Psychology, 12, 97–136.
Tsal, Y., & Benoni, H. (2010). Diluting the burden of load: Perceptual load effects are
simply dilution effects. Journal of Experimental Psychology: Human Perception and
Performance, 36, 1645–1656.
Wilson, D. E., Muroi, M., & MacLeod, C. M. (2011). Dilution, not load, affects distractor processing. Journal of Experimental Psychology: Human Perception and Performance, 37, 319–335.
Wolfe, J. M. (2007). Guided search 4.0: Current progress with a model of visual search.
In W. Gray (Ed.), Integrated models of cognitive systems (pp. 99–119). Oxford: New
York, NY.
Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of a
visual attention and how do they do it? Nature Reviews Neuroscience, 5, 495–501.
Woodman, G. F., Carlisle, N. B., & Reinhart, R. M. G. (2013). Where do we store the
memory representations that guide attention? Journal of Vision, 13, 1–17.

FURTHER READING
Bundesen, C., & Habekost, T. (2008). Principles of visual attention. Oxford, England:
Oxford University Press.
Wolfe, J., & Robertson, L. (Eds.) (2012). From perception to consciousness: Searching with
Anne Treisman. New York, NY: Oxford University Press.

KYLE R. CAVE SHORT BIOGRAPHY
Kyle R. Cave is a Professor of Psychology at the University of Massachusetts
Amherst, where he has been for the past 11 years. As an undergraduate,

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he worked in Stephen Kosslyn’s mental imagery laboratory. He received
his PhD from M.I.T., where Steven Pinker was his advisor. He worked with
Jeremy Wolfe on the first version of the Guided Search model, and most of
his research has centered on the control of covert visual attention and of
eye movements. He has a long-term collaboration with Nick Donnelly and
Tamaryn Menneer of the University of Southampton (United Kingdom) to
understand how representations of target objects and target features guide
attention during search. This work has led to a better understanding of
interference that arises when we try to search for two different items at the
same time, which has practical implications for difficult search tasks such
as airport security screening. He works with Zhe Chen of the University
of Canterbury (New Zealand) on object-based attention, and also on the
relationships between perceptual load, dilution, and attentional zoom.
Personal web site: http://people.umass.edu/kcave
Lab web site: http://psych.umass.edu/VCAlab
RELATED ESSAYS
Mental Models (Psychology), Ruth M. J. Byrne
Multitasking (Communications & Media), Matthew Irwin and Zheng Wang
Resource Limitations in Visual Cognition (Psychology), Brandon M. Liverence
and Steven L. Franconeri
Attention and Perception (Psychology), Ronald A. Rensink
Understanding Biological Motion (Psychology), Jeroen J. A. Van Boxtel and
Hongjing Lu
How Form Constrains Function in the Human Brain (Psychology), Timothy
D. Verstynen



Spatial Attention
KYLE R. CAVE

Abstract
Visual perception requires selective filtering. The process of selecting a portion of the
visual input according to its location is described as spatial attention. Spatial attention has been measured with a wide variety of experimental techniques, including
spatial cuing, spatial probes, distractor interference, ERP, and SSVEP. The results
show that spatial attention sometimes takes the form of a gradient, with strong facilitation of processing within a central region and less facilitation and perhaps even
inhibition in the surround. The positioning of the attentional gradient is controlled
in part by a bottom-up system that directs attention to locations that differ from surrounding locations in basic features. There is also top-down direction of attention,
which favors locations with features matching a defined target. A variety of different experiments have demonstrated that attention can be allocated to a particular
location in the visual field, but another set of experiments show that attention can be
allocated to a visual object, and that attention that is directed to one part of an object
can spread to other parts of the same object. It is difficult to determine whether spatial
attention and object-based attention are controlled by the same system or by separate
systems. Determining the boundaries between different attentional systems should
become easier with the use of ERP data to provide precise timing information about
attentional processes, and fMRI to localize the brain regions controlling attention and
to measure attentional modulation of perceptual processing activity.

INTRODUCTION
Visual perception requires a combination of different processes, from early
processes that detect edges and infer surfaces, to later processes that match
the incoming input to memory representations to achieve recognition. The
earliest processes rely more on local comparisons that can be done with short
neural connections, but the later stages require integration of information
across large parts of the visual field, and thus require that information be
transmitted over long distances within the brain. The earlier processing
stages can produce more information than can be processed by the later
stages, and thus outputs of the earlier states must be filtered to select just
those parts with the highest potential for informativeness before they are
Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

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routed to higher level mechanisms. This filtering process is often labeled as
“attention.”
Visual information arriving at the eye is spread across the two-dimensional
array of the retina, and this spatial organization is, to a large extent, maintained through the early stages of processing. Although many important
types of information are encoded in the early stages, location seems to
play a unique role in the organization of this information, as can be seen in
the spatial maps in the superior colliculus, the lateral geniculate nucleus,
primary visual cortex, and other brain regions serving vision. Location also
plays an important role in visual attention.
FOUNDATIONAL RESEARCH
SPATIAL CUING
One obvious reason why location is important in visual attention is that
visual information at the center of gaze is projected onto the fovea, which
has the highest spatial resolution within the retina. Thus, an important
part of selecting visual information is pointing the eyes toward the most
informative location in the environment. However, spatial cuing experiments (Eriksen & Hoffman, 1974; Posner, Snyder, & Davidson, 1980) have
shown that this overt attention is not the whole story. Even without moving
the eyes, it is possible to select one part of the visual field for faster, more
detailed processing. In these experiments, subjects are asked to keep their
eyes fixed at one location, while a cue appears some distance away, signaling
that an upcoming stimulus is most likely to appear at that location. This
cue causes covert attention to be allocated to that location, so that when the
stimulus does appear, subjects will respond to it more quickly if it is at the
cued location, and more slowly if it appears elsewhere.
There are two different aspects to this spatial cuing effect on attention.
If, throughout the course of the experiment, the stimulus appears more
often at the cued location than somewhere else, then the cue is providing useful information that can improve performance. In many of these
experiments, the cue is a symbol appearing at the center of gaze, and
subjects must interpret the symbol to know which location should be
attended. As long as the cue is informative, subjects have an incentive
to interpret the symbol and move their spatial attention to the indicated
location. This internally motivated cue use is called endogenous orienting.
In other cases, a cue can move attention to a location even if the subject
believes that it is uninformative. For this exogenous orienting, the cue
must be a flash or other salient stimulus located at the location to be
cued.

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SPATIAL PROBES
The simple spatial cuing paradigm has been a foundation on which other
more complex experimental procedures have been built. The stimulus that
triggers the response can be thought of as a probe that measures attention at
a location. Across trials, it can be applied to many different locations to produce a full picture of attentional allocation. The simple cue can be replaced
with other more complex stimuli coupled with tasks requiring spatial attention. The first example of this came from Hoffman and Nelson (1981), who
combined a probe task with a letter search task. Reports of the probe stimulus were more likely to be correct if it appeared near a correctly reported
target of the letter search. Spatial attention allocated to the letter target apparently also improved discrimination of the probe stimulus if it was in the same
vicinity. This experiment, and the many probe experiments that followed,
demonstrated the general nature of spatial attention, enhancing the processing of any stimulus appearing within the selected region. This spatial aspect
of attention led Posner, Snyder, and Davidson (1980) to compare attention to
a spotlight that illuminates just one selected part of the visual field.
FLANKERS AND DISTRACTOR INTERFERENCE
The importance of location in attention is made apparent by a technique used
by Eriksen and Eriksen (1974). They simply required subjects to identify a letter appearing in the middle of the visual field. Other letters appeared along
with the target letter, and although the locations of these letters made it clear
that they were not the target, these letters could affect the response if they
were close enough to the target location. If these flanker letters were associated with the same response as the target, then the response was faster, and
if the flankers were associated with a different response, then the response
was slower. If the flankers were close to the target (within 1∘ of visual angle),
they were able to activate responses to the point that they either facilitated or
competed with the response being activated by the target letter. This flanker
effect shows that spatial selection is not perfect, and that distractors are not
always fully excluded.
GRADIENT VERSUS MOVING SPOTLIGHT
Experiments by Downing (1988) and by Laberge and Brown (1989) showed
that attentional facilitation could take the form of a gradient, with stronger
perceptual sensitivity for locations nearer the cue, and a fall-off in sensitivity
with distance. Sperling and Weichselgartner (1995) argued that this area of
attentional facilitation can be deallocated from one location and reallocated to
a new location without selecting locations in between. For a detailed review

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of the relevant findings on shape and movement of the attentional gradient,
see Cave and Bichot (1999).
ATTENTIONAL CAPTURE AND BOTTOM-UP ATTENTIONAL CONTROL
One big challenge for the visual system is deciding where in the visual field to
allocate the gradient of spatial attention in order to be most effective. Given
that this decision must be made before visual processing is completed and
before objects have been identified, it has to be done with only partial information. This control of attention requires a balance between different factors,
but one important factor is the presence of featural variation in the visual
field. Spatial attention is often allocated to a location that differs from its
surrounding locations in the basic visual features present there. Attention is
often captured by a location with a red stimulus that is surrounded by green,
or a horizontal contour that is surrounded by vertical, or a moving object
that is surrounded by stationary objects. Experiments by Theeuwes (1992)
demonstrate that attention can be captured by unique features (singletons)
even if they are irrelevant to the current task.
This attentional capture shows the importance of stimulus-driven or
bottom-up factors in controlling attention. However, Folk, Remington, and
Johnston (1992) have shown that attentional capture can be prevented in
some circumstances. To reconcile these results, Bacon and Egeth (1994)
proposed that the attentional system can shift modes depending on the
needs of the task. When a target object differs from the distractors in some
basic feature, searchers may simply use “singleton detection mode,” in
which attention is captured by any item that has a unique feature that differs
from its surroundings. Thus, when Theeuwes’ subjects search for a shape
singleton (diamond target among circle distractors), their attention will be
captured by a color singleton (red among green). However, if the task makes
it difficult to find the target by singleton search, searchers may instead
switch to “feature search mode,” in which attention is allocated to those
locations that have a specific feature value known to belong to the target.
TOP-DOWN ATTENTIONAL GUIDANCE AND THE TARGET TEMPLATE
The ability to search for a specific feature is another important factor in
the control of spatial attention: Many visual tasks require that attention
be directed to locations that have a specific color, size, or other feature,
even though that feature may not be a unique singleton. This top-down
guidance toward known targets must be balanced against the bottom-up
capture by unique objects. The top-down guidance requires that some sort
of internal target definition be maintained in order to guide attention. This

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target representation has sometimes been called the “target template,”
although some tasks require that it be more general than implied by the
term “template.”
Because the target representation is active only for the course of a particular visual task and will change from on task to another, it is natural to
compare it to visual working memory, the temporary storage proposed by
Baddeley (2007) to hold visual information that is actively being used in cognitive tasks. Perhaps the target information that guides attention top-down is
stored in the same visual working memory that is used for other visual tasks
that require temporary storage. If the search target representation and visual
working memory are one and the same, then whenever something is stored
in visual working memory for a nonattentional task, we might expect attention to be captured by stimuli that match the stored information. This idea
has been tested with various different search and memory tasks. In some circumstances, holding an item in visual working memory does redirect search,
while in other circumstances it does not (Olivers, Peters, Houtkamp, & Roelfsema, 2011; Woodman, Carlisle, & Reinhart, 2013). There is some type of
link between visual working memory and the attention target representation, because one can interfere with the other under the right conditions, but
they are probably not one and the same thing.
OBJECT-BASED ATTENTION
Although location is very important in allocating attention, there is also
abundant evidence that attention can be shaped by object boundaries. When
two objects are superimposed, one can be selected over the other (Duncan,
1984), and when an attended object moves, attention can move with it
(Kahneman, Treisman, & Gibbs, 1992). These demonstrations have led to a
distinction between spatial attention, which is allocated to a location, and
object-based attention, which is allocated to an object representation.
Many of the experiments in object-based attention have focused on how
attention that is initially cued to one part of an object can spread to other
parts of the same object. Egly, Driver, and Rafal (1994) provided a useful
experimental paradigm for studying this aspect of object-based attention by
extending Posner’s cuing procedure. Posner originally placed two boxes in
the stimulus display (one on each side of fixation), and cued one of them as
the expected target location. Egly, Driver, and Rafal extended these boxes
to make them long narrow rectangles, and then cued just one end of one
rectangle. The test stimulus, to which subjects responded as quickly as
possible, appeared in one end of one of the two rectangles. Responses were
fastest when it appeared at the cued end, as expected from Posner’s original
experiments. However, responses were faster for a stimulus at the uncued

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end of the cued rectangle than for a stimulus on the uncued rectangle, even
though distance from the cue was the same for both stimuli. Attention at the
cued location spread to facilitate visual detection of other locations within
the same object. See Chen (2012) for a review of object-based attention.
Although this type of object-based attention is easy to demonstrate experimentally, it does seem to require that attention be spread broadly across
a large area (Goldsmith & Yeari, 2003), and that the objects be visible long
enough for them to be interpreted as separate objects (Chen & Cave, 2008).
Object-based attention also varies according to whether the stimulus configuration is described as one object or two (Chen, 1998). Thus, even though
the object organization of a scene can affect attention when the objects are
irrelevant to the task, encoding the object organization is apparently not a
necessary step in allocating attention.
The relationship between location-based attention and object-based attention is not clear. They could arise from separate attentional mechanisms
working at different processing stages within the visual system. Selection
that occurs within the early processing mechanisms of the lateral geniculate
nucleus and primary visual cortex could be responsible for location-based
attention, while selection among more abstract object representations in
temporal regions could be producing object-based attention. On the other
hand, there might be a single spatial selection mechanism, with the locations
that are selected being shaped by the perceived object organization. This
idea of a unified spatial/object selection is consistent with theories in which
attention is driven by an interaction between low level visual processing
and higher level object representations (Heinke, Mavritsaki, Backhaus, &
Kreyling, 2009).
VISUAL SEARCH
Cuing experiments, in which the target location is known or at least expected
in advance, have demonstrated both location selection and object selection.
As important as attention is in these relatively simple tasks, it is probably
even more important in search tasks, in which the target location is unknown
and the allocation of attention is probably much more complex in search.
Most search experiments do not address the role of spatial location in selection, but instead test the capacity limits of attention by adding more and more
objects to the search array. These search experiments have been important in
exploring the perceptual limitations that make attentional selection necessary (Treisman & Gelade, 1980; Wolfe 2007). Search experiments have been
the primary tool for determining which visual properties are identified early
in processing and can effectively guide attention (Wolfe & Horowitz, 2004).

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Although search has not been used as much to demonstrate the spatial
nature of visual selection, it is pretty clear that spatial selection plays a role
in search. Many visual search experiments elicit a combination of eye movements and covert attention. The eye movements are clearly an instance of
spatial selection, given that the goal of the eye movements is to direct the
fovea toward the selected location. The role of covert attention in search can
be studied by eliminating the eye movements, either by using an eyetracker
or by presenting the search array so briefly that an eye movement cannot
be programmed and executed before it disappears. Spatial selection can be
demonstrated in these covert search tasks with spatial probes: Probes at target locations or at locations that share target features show attentional facilitation, even though the probes do not share the target features, and are only
linked to those features by location (Kim & Cave, 1995).
CUTTING-EDGE RESEARCH
ERP, MEG, AND SSVEP
The history of research in spatial attention illustrates that much can be
learned with behavioral experiments measuring response times and accuracy. However, event-related potential (ERP) methods based on measuring
changes in electrical potential with scalp electrodes have provided a powerful tool for measuring how neural processing of visual signals changes
with attention (Luck, Woodman, & Vogel, 2000; Mangun & Hillyard, 1995).
The attentional enhancement of visual signals can be measured in ERPs
within 100 ms or so after a stimulus appears. ERP methods also provide a
way to measure attention at visual field locations that the subject is trying
to ignore, which cannot be done with spatial probes that require a response.
Also, experiments by Hopf et al. (2006) using a related method based
on magnetoencephelography (MEG) have provided key demonstrations
of the inhibitory attentional surround around attended locations, which
corresponds to behavioral findings by Cave and Zimmerman (1997) and by
Mounts (2000).
The electroencephalographic measurements used in ERP experiments can
also be used to record steady-state visual electric potentials (SSVEPs), which
can also reflect changes in neural activation caused by attention (Muller,
Malinowski, Gruber, & Hillyard, 2003). In this paradigm, each stimulus in
a visual display flickers at a different rate, and those stimulus oscillations
are carried by the neural signals encoding those stimuli. When a particular
stimulus is attended, the EEG signal will show a stronger oscillation at that
stimulus’ frequency. Thus, this method provides another way to measure
spatial attention without a response from the subject.

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SPLIT ATTENTION
Many of the experiments described here have started with the assumption
that spatial attention selects a single unified region within the visual field.
In fact, that assumption is built into the spotlight metaphor that drove early
attentional research. However, many visual tasks require comparing or conjoining stimuli at two or more separate visual field locations, and the question arises whether those multiple locations can be selected without selecting
distractor locations between them. A number of experiments have been presented over the years to demonstrate split attention, but it has been difficult
to determine whether attention is simultaneously selecting to locations, or is
moving quickly between them. Jans, Peters, and De Weerd (2010) have thoroughly reviewed these experiments and have tried to interpret them as the
product of a single focus of attention. The theoretical assumptions that are
necessary to defend the single attentional spotlight hypothesis require such
complex operations that the split attention alternative begins to sound more
plausible (Cave, Bush, & Taylor, 2010).
PERCEPTUAL LOAD VERSUS DILUTION
One of the more controversial general theories of attention comes from Nilli
Lavie (2005), who suggests that there is a fixed amount of attentional capacity
that can be allocated to different visual tasks, and that at any one moment,
all of it will be used. This means that if the current visual task is relatively
easy and uses only some of the available capacity (in other words, it has a
low perceptual load), the rest will be applied to processing distractor items
in the visual field, even though they are irrelevant to the current task. Lavie
provides supporting evidence for this perceptual load theory from a number of experiments. She shows that the interference from a salient distractor
decreases as the task requires processing of more items.
Perceptual load theory has faced a number of challenges. One of the more
notable comes from Tsal and Benoni (2010) and Wilson, Muroi, and MacLeod
(2011), who reject Lavie’s claim that it is the extra perceptual load from additional relevant display items that absorbs attentional capacity and limits distractor interference. Instead, they propose that whenever items are added
to the display, even if they are irrelevant to the task, they interfere with the
processing of other items. This alternative account is referred to as dilution.
Comparing the evidence for perceptual load theory against the evidence
for dilution is complicated by another factor, as pointed out by Chen and
Cave (2013). In these studies, the search array generally appears suddenly,
and these abrupt onsets have the effect of broadening the attentional zoom
to encompass the full display. When the display is presented in a way that
avoids the abrupt onsets, the results no longer show the general pattern of

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dilution. That does not mean that perceptual load theory prevails, as a number of other studies have challenged it, including one by Kyllingsbaek, Sy,
and Giesbrecht (2011) showing that adding distractor letters can take processing resources away from targets. There may be validity in Lavie’s general
claim that processing of distractors varies according to the demands of processing targets, but the whole story is probably more complicated.
LOCALIZING BRAIN MECHANISMS FOR SPATIAL ATTENTION
The focus here has been mainly on behavioral studies of attention, and on
ERP studies that provide timing information about the neural processing
underlying attention. These results can now be combined with a large number of functional MRI studies showing which brain regions are involved in
attentional selection. The relevant brain regions are often organized into two
categories. The “sites of attention” are those brain regions within the visual
system that are responsible for identifying objects, including primary visual
cortex (V1) and the ventral, or “what” pathway. The activity within these
regions is modulated according to attentional goals (Kastner & Pinsk, 2004).
That modulation seems to be controlled by another set of cortical regions
often described as “sources of attention,” which include frontal and parietal
regions that are linked together in such a way that they are often referred to
as the frontal-parietal network (Corbetta, Patel, & Shulman, 2008).
Interpretation of these studies of large-scale brain activation can be guided
by measurement of attentional effects on individual neurons (Moran &
Desimone, 1985). When these neuroscience findings are combined with the
decades of research on attentional performance described earlier, we have a
rich environment within which to construct detailed theories of attentional
selection.
KEY ISSUES FOR FUTURE RESEARCH
ATTENTIONAL ZOOM
Over the years, a number of detailed computational models have been proposed to explain how the attended location is chosen, but these models have
had less to say about how the size of the attended area can be adjusted according to the task. Nonetheless, there are clear demonstrations that attention
can zoom in to a small region for difficult tasks, and can pan out to select a
wide area for easier tasks (Eriksen & St. James, 1986; Laberge, 1983; Larsen &
Bundesen, 1978). More recently, Rijpkema, van Aalderen, Schwarzbach, and
Verstraten (2008) have used brain imaging to show that cortical regions with
different receptive field sizes can be activated to match the attentional zoom

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settings required for different visual tasks. Models of attention need to be
expanded to capture this adjustment of attentional zoom more fully.
DIFFERENTIATING ATTENTIONAL MECHANISMS
As noted earlier, it is usually difficult to determine the extent to which the
task of visual selection is divided across separate mechanisms. For instance,
are spatial attention and object attention performed by a single system or two
separate systems? Are there different selection mechanisms working at different levels of the hierarchy within the visual system? Or does attentional
selection require coordination between lower and higher levels of visual processing? The behavioral methods that have been used to explore these questions for some time can now be augmented with localization information
from fMRI and timing information from ERP studies in order to find the
boundaries between the different parts of the attentional system. This line of
enquiry may also provide a better understanding of the computational limitations within the visual system that make attentional selection necessary in
the first place.
ATTENTION AND CONSCIOUSNESS
Spatial attention seems to be necessary to prevent the visual system from
being overwhelmed by the amount of incoming retinal input to be processed.
However, it has been natural to assume that this selection mechanism also
serves as the gateway to visual consciousness. Perhaps everything that is
selected makes its way into our awareness, while everything not selected
remains outside of conscious. That assumption, however, is contradicted by
evidence showing that visual stimuli can be selected without making it into
awareness. One unusual example comes from Jiang, Costello, Huang, and
He (2006), in which nude images draw attention to their location without the
observer’s awareness. Thus, visual selection and consciousness must be separate, and even when a stimulus is selected within the visual system, it may
still not be able to pass through the higher level gateway into awareness.
Koch and Tsuchiya (2007) suggested that there might be a pathway for stimuli to enter consciousness without being selected by spatial attention, based
on the finding by Li, VanRullen, Koch, and Perona (2002) that animals and
vehicles could be detected in scenes while attention was occupied in a different part of the visual field. While it is clear that performance on the detection
tasks can be surprisingly good, it is not clear that it is done without any contribution from spatial attention (Cohen, Alvarez, & Nakayama, 2011). Thus, the
full relationship between spatial attention and conscious experience remains
to be fully worked out.

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FURTHER READING
Bundesen, C., & Habekost, T. (2008). Principles of visual attention. Oxford, England:
Oxford University Press.
Wolfe, J., & Robertson, L. (Eds.) (2012). From perception to consciousness: Searching with
Anne Treisman. New York, NY: Oxford University Press.

KYLE R. CAVE SHORT BIOGRAPHY
Kyle R. Cave is a Professor of Psychology at the University of Massachusetts
Amherst, where he has been for the past 11 years. As an undergraduate,

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he worked in Stephen Kosslyn’s mental imagery laboratory. He received
his PhD from M.I.T., where Steven Pinker was his advisor. He worked with
Jeremy Wolfe on the first version of the Guided Search model, and most of
his research has centered on the control of covert visual attention and of
eye movements. He has a long-term collaboration with Nick Donnelly and
Tamaryn Menneer of the University of Southampton (United Kingdom) to
understand how representations of target objects and target features guide
attention during search. This work has led to a better understanding of
interference that arises when we try to search for two different items at the
same time, which has practical implications for difficult search tasks such
as airport security screening. He works with Zhe Chen of the University
of Canterbury (New Zealand) on object-based attention, and also on the
relationships between perceptual load, dilution, and attentional zoom.
Personal web site: http://people.umass.edu/kcave
Lab web site: http://psych.umass.edu/VCAlab
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